ADOPTING AN OPEN SOURCE HOSPITAL INFORMATION SYSTEM …

LIFE: International Journal of Health and Life-Sciences

ISSN 2454-5872

Available Online at: http://grdspublishing.org/

38

Bouidi et al., 2017

Volume 3 Issue 3, pp. 38-57

Date of Publication: 18th December 2017

DOI-https://dx.doi.org/10.20319/lijhls.2017.33.3857

This paper can be cited as: Bouidi, Y, Azzouzi Idrissi, M & Rais, N. (2017). Adopting an Open Source

Hospital Information System to Manage Healthcare Institutions. LIFE: International Journal of Health

and Life-Sciences, 3(3), 38-57.

This work is licensed under the Creative Commons Attribution-Non Commercial 4.0 International

License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/4.0/ or send a

letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.

ADOPTING AN OPEN SOURCE HOSPITAL INFORMATION

SYSTEM TO MANAGE HEALTHCARE INSTITUTIONS

Youssef Bouidi

Laboratory of Informatics, Modeling and Systems (LIMS), University of Sidi Mohamed Ben

Abdallah (USMBA), Fez, Morocco

[email protected]

Mostafa Azzouzi Idrissi



[email protected]

Noureddine Rais



[email protected]

Abstract

Our paper is a comparative study of different Open Source Hospital Information Systems

(OSHISs). We chose open source because of problems in healthcare management like budget,

resources and computerization. A literature review did not allow us to find a similar comparison,

which explains the great interest of our study. Firstly, we retrieved nine OSHISs: MediBoard,

OpenEMR, OpenMRS, OpenHospital, HospitalOS, PatientOS, Care2x, MedinTux and HOSxP.

Then, we used the DeLone & McLean model to evaluate information systems qualities and the

SQALE method for the technical evaluation. Finally, we get OSHISs activities using open source

mailto:[email protected]





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community statistics. In application, we used SonarQub as a SQALE implementation. As results,

we get six characteristics for MediBoard (respectively OpenEMR, OpenMRS, OpenHospital,

HospitalOS, PatientOS, Care2x, MedinTux and HOSxP), with a technical debt of 42.16%

(respectively 53.23%, 54.5%, 65%, 66.1%, 65.2%, 56.96%, 52.13% and 75.5%). Activities

statistics prove the MediBoard potential with 2381 commits and 12 contributions in 2016. Based

on these results, we chose MediBoard as a solution to adapt in healthcare organizations. It is

also a challenge to prove open source power in health management. As a future work, we will

implement and test MediBoard modules in a real case.

Keywords

Health System, Hospital Information System, Open Source, SQALE, Technical Debt.

1. Background

Healthcare systems suffers from several problems and obstacles that disrupt the evolution

of the healthcare sector. The health organization has three levels, depending on the means, the

patient states and the locality. In this work, we treat the first and second level. Our study focuses

on rural clinics (RC), health centers (HC), provincial hospitals (PH) and regional hospitals (RH).

This study is only one part of the integration of a HIS with the main problems affecting

the health sector, such as lack of computerization, lack of budget and lack of resources. Indeed, it

is a comparison of the OSHISs to choose the one that meets our needs and adopt it in healthcare

institutions.

2. Introduction

Healthcare system complexity defines an organizations management problem.

Therefore, it is necessary to use an Information System (IS) to make healthcare institutions

management easier. Developing countries have not yet computerized its public healthcare

service. This is because of the lack of resources and budget. The World Health Organization

(WHO) released a report confirming the weakness of resources, the lack of investment, a very

limited budget dedicated to care and the absence of a comprehensive strategy for public health

research management and governance (World Health Organization, 2016). However, this

service requires an IS that manages its various institutions and organizations. Nevertheless, the

IT market offers us several solutions: commercial IS, free IS, complete IS, incomplete IS and

open source IS. From there, we came up with the idea of using an open source solution.


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The computing world has an increase in Open Source activity. Several software,

Enterprise-Resource-Planning (ERP) and IS are developed under open source license to ensure

freedom of use, modification and redistribution. Healthcare sector has also experienced several

IT solutions. Here we are talking about the Hospital Information System (HIS), a set of

technological tools that manage hospital data, such as patient information, services, doctors,

nurses and logistics data. According to (Hannah & Ball, 2004), HIS is an application developed

to manage the medical, administrative, legal and financial aspects of the hospital.

Open Source contribution in healthcare has given birth to OSHISs which are defined in

the same way as in the HIS (Hannah & Ball, 2004), but they enjoy the benefits of activities

freedom. Currently, there are several OSHISs with different qualities. Indeed, there is a

divergence between OSHISs in terms of services, functional coverage, types and licenses. For

this reason, we will have to compare OSHISs and choose the one adapted to our needs.

However, a bibliographic study did not allow us to find any reference to an old comparison.

This is the great interest of our study.

In this paper, we start by presenting a literature review, stating the history of these

systems and some research cases and real experiences. Especially, the Malian experience, made

by Cheick Oumar Bagayoko (Cheick-Oumar, Dufour, Chaacho, Bouhaddou, & Fieschi, 2010).

Then, in the materials section, we present the OSHISs that we will compare using the detailed

method in the specified section. In fact, we use the DeLone & McLean Model of IS quality

(DELONE & MCLEAN, 2003) and the SQALE Method for the technical debt (Letouzey J. L.,

2012) using the Sonar platform as SQALE implementation. We used also Open Source

activities statistics. After the comparison, we discuss the results and give interpretations and

explanations. Finally, the last section, we conclude our article with a global and final synthesis,

and then declare our future work.

3. Literature Review

The first HIS was developed in 1965 by Lockheed Martin when he initiated a project to

collect information on these systems (Lockheed Aircraft Corporation, 1965). Lockheed has built

a HIS prototype called the Medical Information System (MIS) and tested by El Camino

Hospital (Lockheed Aircraft Corporation, 1965) (Gall, Norwood, & Hospital, 1977). Initially,

HIS was limited in personnel and finance management. He then began to integrate the medical


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aspect of health care institutions by creating the Medical Information System (MIS), also known

as the Clinical Information System (CIS) (Degoulet, 1998) (Ashish, 2008). In the 1970s and

1980s, other hospitals around the world used HIS (Krobock, 1984) with integrated capabilities

such as instrument planning, recording and automation (Rubinoff & Yovits, 1977). In the

1990s, Japan used HIS to the maximum extent of hospital activities, including the preparation

of health recovery insurance. In 1991, 81.6% of all Japanese hospitals used health informatics

technology (Yoshikawa & Ishikawa, 1995) (Miyake, 1987). The integration of HIS with

insurance association systems has also been prototyped, creating the potential for more

comprehensive databases on patient medical records (Yoshikawa & Ishikawa, 1995). During

this period, hospitals and developers focused on two specific objectives: Adapting the system to

the clinical environment and establishing communication between HIS and other external

entities (Yoshikawa & Ishikawa, 1995). The integration of HISs was still difficult because of

the diversity of tasks, technical limitations, preference for departmental systems and the

philosophy of developers. In this integration process, another important key was the execution

of synchronous updates between heterogeneous systems and the management of communication

servers (Smith, 1999) (Lenz, Blaser, & Kuhn, 1999) (Stuewe, 2002). During the 2000s,

component-based, communication, distributed systems and network architectures enabled the

development of a new type of HIS that improves communication standards and provides an

interoperable environment for electronic health records (EHR) (Van de Velde & Degoulet,

2003).

The African experience with OSHISs has also been present in several countries.

OpenMRS was the challenge of Paul Biondich and Burke Mamlin to guarantee health care

access in Kenya and to fight diseases that destroy the lives of its citizens. The health situation in

Kenya in 2004 prompted Paul and Burke to adopt Open Source as a solution in front of the

country's financial situation and lack of resources (OpenMRS LLC, 2014). In Mali, adopting an

OSHIS was a project in which Cheick Oumar Bagayoko was able to test MediBoard in 2010

(Cheick-Oumar, Dufour, Chaacho, Bouhaddou, & Fieschi, 2010). Bagayoko has proved the

entirety of OSHIS by comparing the MediBoard’s functionalities with the complete HIS used

by the University Hospital of Marseille in France that we present its results in appendix 1. After

installing it on two servers, one for testing and validation and the other for implementation and

deployment, Cheick Oumar evaluated aspects of the ease-of-use and the user’s (Cheick-Oumar,


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Dufour, Chaacho, Bouhaddou, & Fieschi, 2010). Bagayoko obtained, as result of this

experiment, five fully implemented modules as shown in Table 1, and a widely accepted system

that we show the rates of obtained responses in Table 2.

Table 1 : The implemented modules of MediBoard - Mali (Cheick-Oumar, Dufour, Chaacho,

Bouhaddou, & Fieschi, 2010)

Modules implemented in MediBoard

Management of the Patient's Medical Record

Management of the Patient Administrative Record

Tracking Practitioners' Activities

Infrastructure Management

Billing System (Entirely Developed)

Table 2 : The use feedback of MediBoard - Mali (Cheick-Oumar, Dufour, Chaacho, Bouhaddou,

& Fieschi, 2010)

System Criteria Rate of responses

Useful system 77%

Easy system 85%

Increased reliability of data 100%

Continuation of the experiment 100%

4. Materials

In this study, we choose nine OSHISs to compare their quality and define the best of

them. We retrieved their source code using the SourceForge platform (SourceForge, 2017), their

documentation using their official websites and their statistics using the OpenHub platform.

OpenMRS: It is a collaborative project designed to manage healthcare, especially, in

developing countries. OpenMRS was a response to many challenges like the serious diseases

(HIV, Malaria). Paul Biondich and Burke Mamlin from the Indiana University School of

Medicine created this system in 2004. They had this idea after their academic visit to Kenya for

offering them an access to health care project. It has many collaborators in different specialties as

volunteers. OpenMRS exist actually in many countries around the world for research, clinical

use, development, evaluation and other uses. (OpenMRS LLC, 2014)

OpenEMR: It is an Electronic Health Record for a medical practice management. It is

ONC Complete Ambulatory EHR Certified with international uses. It was originally developed

by Syntech organization in 2001 as Medical Practice Professional like version 1.0. Actually, the


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system is on version 5 since 2017 and its code repository was migrated to the GitHub

(OpenEMR Project, 2012)

MediBoard: It is an open source web application designed to manage health

establishments. It is a Hospital Information System created by Thomas Despoix and Romain

Ollivier. This HIS is actually until version 0.4.0 developed by the OpenXtrem organization. It is

a modular system based on web technologies to handles all patient files, workflows and planning

of all health establishment activities. (MediBoard, 2014)

HospitalOS: It is a HIS and a research / development project designed to every small-

sized hospital. Hospital OS was created and developed for Thailand community. It is actually

until 3.9 version and it is featured especially by the treatment of patients. (Webster, 2011)

Care2x: It is an integrated HIS started as “Care 2002“project in 2002. The first official

release was until version 1.1 in 2004. In 2003, the project name was changed to Care2x. The last

stable release was in 2012 until version 2.6.29. Its design can handle both of medical and non-

medical services. Care2x has many features that include especially the smart search and the

multiple custom languages. (care2x, 2013)

OpenHospital: It was developed by Informatici Senza Frontiere, in collaboration with

students of Volterra San Donà di Piave Technical highschool, in 2005. It was implemented at St

Luke’s Hospital, Angal, in Nebbi District, Northern Uganda. It was used also in Kenya,

Afghanistan, Benin and Congo. Actually, this HIS is at its seventh release, which is multi-user,

has an extended patient database, has a historical integrated patient and gives an internal

communication, reports and statistics. (Informatici Senza Frontiere, 2014)

MedinTux: It was initiated by the doctor Roland Sevin since ten years. It is distributed

under the CeCiLL V2 license which is equivalent to the GPL license adapted to the French

legislation. It was originally written for French emergency services, it can be used in a multi

users environment and offers many features like consultations, prescriptions, real time

visualization and statistics (MedinTux, 2012)

HOSxP: It is a HIS used in over 70 hospitals in Thailand. It was called KSK-HDBMS.

Its development started in 1999 by Suratemekul to be continued by employers of its company

Bangkok Medical Software. It is distributed under a GPL license and free only for its Primary

Health Care Unit version. (SourceForge, 2002)


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PatientOS: It is a HIS for small hospitals and clinics. It is a web-based application under

the GPL license. (SourceForge, 2007)

5. Method

After collecting the source code of the OSHISs, we move to the stage of examining them.

This comparative study concerns their qualities, so we will evaluate them to select the best one to

adopt. The DeLone & McLean model offers three dimensions of IS quality evaluation. Initially,

in 1992, this model defined only the system and information quality as the two only dimensions

that judged the IS quality (DELONE & MCLEAN, 2003).

Figure 1: The first model of DeLone & McLean (DELONE & MCLEAN, 2003)

An easy access, a short response time and practical tools for users determine the system

quality, which contributes to a more efficient work. The information quality produced is

determined by information accuracy, accessibility, completeness and reliability.

However, as the figure 1 shows, this model cannot judge the IS quality without use,

examination of user satisfaction and verification of impact on the concerned organization. For

this reason, this model was improved in 2003 by adding a third dimension concerning quality of

service (DELONE & MCLEAN, 2003).


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Figure 2: The improved model of DeLone & McLean (DELONE & MCLEAN, 2003)

This model was implemented in another one that specify clearly the third dimension. As

mentioned in the figure 3, directly or indirectly, the service quality plays an essential role in IS

quality evaluation. It is defined directly by the IS technical support and indirectly by the system

and the information qualities. (Bharati & Berg, 2005)

Figure 3: The service quality Model of a management information system (Bharati & Berg,

2005)

Technically speaking, the technical measures of an IS define directly the provided service

to final users. SQALE method is a method that measures technical quality using technical debt


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concept. The system and information define also, indirectly, the service quality through the IT

performance of the organization's employees.

The SQALE method is based on the technical debt concept, which consists of measuring

the quality indices of the technical IS characteristics after having analyzed them. The quality

indicators present these measures by defining the technical debt that characterizes each of IS

characteristics. (Letouzey J.-L. , 2016)

Figure 4 : The SQALE method structure (Letouzey J. L., 2012)

The quality model proposed by this method aims to organize the non-functional

requirements related to the quality of the code. It is organized in three hierarchical levels. The

first level is composed by derived characteristics coming from quality standards as factors to

describe the source code quality, such as stability, reliability, changeability, efficiency, security,

maintainability, portability and reusability. The second level, called sub-characteristics, used to

combine requirements groups in two types: those that correspond to life cycle activities and those

generally recognized as taxonomic results. The third level includes the requirements of the

internal source code attributes. (Letouzey J.-L. , 2016)


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Figure 5 : The quality model levels of the SQALE Method (Letouzey J.-L. , 2016)

Figure 6 : The characteristics of SQALE quality (Letouzey J.-L. , 2016)

According to Jean-Louis Letouzey (Letouzey J.-L. , 2016), the SQALE analysis model

performs two main tasks: the first applies rules to standardize measures by transforming them

into costs and the second sets rules to aggregate these standardized values. The SQALE method

defines the cost aggregation rules either in the quality model tree or in the artefact hierarchy of

source code.

The indices of this method represent the costs and they are measured on the same scale in

order to manipulate all authorized operations for this kind of scale. Jean-Louis Letouzey

confirmed that the characteristic indices of SQALE are the Testability Index (STI), Reliability

Index (SRI), Changeability Index (SCI), Efficiency Index (SEI), Security Index (SSI),

Maintainability Index (SMI), Portability Index (SPI) and Reusability Index (SRuI) (Letouzey J.-

L. , 2016).


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By summing all remediation costs, related to all quality model requirements, the

remediation cost of all quality model characteristics can be estimated. This measure is the

SQALE Quality Index: SQI. The SQALE quality index is an implementation of the associated

technical debt concept to the source code.

The SQALE method defines four indicators related to the quality characteristics, allowing

a highly synthesized representation of the IS quality (Letouzey J.-L. , 2016). The SQALE rating

consists to produce a derived measure or an ordinal scale subdivided in five levels from A

(Green) to E (Red). The Kiviat diagram consists to present the SQALE evaluation in concentric

areas and targeting the quality of each project according to its values. It presents in the same

diagram all compared projects characteristics ranking according to the quality model. The

SQALE pyramid helps to make appropriate decisions with considering the dependence between

quality characteristics model and the IS life cycle. The fourth indicator is the SQALE Debt Map,

which represents the artefacts of the assessment scope drawn on two dimensions: the first is the

technical debt (SQI) and the second is the business impact (SBII). (Letouzey J.-L. , 2016)

Figure 7 : The quality indicators of SQALE method (Letouzey J. L., 2012) (LETOUZEY, 2014)

To implement this method we used the SonarQub platform (SonarSource, 2017). It has a

scanner that analyzes the source code to determine the characteristics and attribute them their

technical debt scores. This platform respects the Client-Server architecture. In the server, the

SQALE method is implemented in order to evaluate the source codes and to send to the Client


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the measures to be presented in indices form and indicators that allow us the subtraction of the

according technical debt to each characteristics.

Concerning system and information quality measurements, there are several models that

implement the DeLone & McLean model. The implementations DeLone & McLean (2003,

2004) and Holsapple & Lee-Post (2006) have confirmed the criteria that allow the system and

information evaluation. These judgments have to be recovered from the final users of IS.

Figure 8 : Holsapple & Lee-Post model (Dorobat, 2014)

In our work, we will only examine the technical side in order to compare the OSHISs and

judge their service qualities. After loading the source code in the SonarQub platform, we

analyzed each of the measurements retrieved by the Sonar server that implements the SQALE

method. Subsequently, we recovered the measures and indicators that we will present in the next

section and discuss them in order to confirm the choice of the good OSHIS.


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On the other hand, because we are working on open source solutions, it is necessary to

compare the OSHISs activity. To accomplish this step, we used the OpenHub platform, which

presents the Open Source community feedback by statistics form. Its statistics set up two

important criteria; we are talking about contributions and commitments. Therefore, to examine

the OSHISs activity, we will compare the two criteria retrieved directly from the Open Source

community. (Black Duck Software, 2016)

6. Results

The method mentioned in the previous section allowed us to have a set of results that

prove the technical potential of MediBoard among other OSHISs. The measurements obtained

from the SonarQub platform were Reliability, Security, Maintainability, Complexity,

Documentation and Rules Compliance.

Technically speaking, the SQALE method implementation, SonarQub, has determined

six characteristics that have been evaluated for MediBoard (respectively OpenEMR, OpenMRS,

OpenHospital, HospitalOS, PatientOS, Care2x, MedinTux and HOSxP) with a debt of 42.16%

(respectively 53.23%, 54.5%, 65%, 66.1%, 65.2%, 56.96%, 52.13% and 75.5%) for the SQALE

Quality of Technical Support. In Table 3, we present the details of the obtained results recovered

from the SonarQub for each OSHISs.

Table 3: Classification of OSHISs according to their SQALE quality debts

OSHISs Reliability Security maintainability RC Complexity Documentation SQ

MediBoard 36,4% 24,8% 21,4% 70,8% 2,4% 97,2% 42,16%

MedinTux 60,6% 43,2% 27% 80,2% 23,2% 78,6% 52,13%

OpenEMR 62% 42,8% 25% 89% 4,2% 96,4% 53,23%

OpenMRS 58,4% 65,4% 26,8% 58,4% 20,6% 97,4% 54,5%

Care2x 56% 80,6% 24,4% 83% 38,8% 59% 56,96%

OpenHOspital 64,6% 62,4% 74,6% 95,4% 13,6% 79,4% 65%

PatientOS 73,4% 62,8% 43,4% 72,8% 48,6% 90,2% 65,2%

HospitalOS 74,2% 56,4% 63,6% 65,4% 41,4% 95,6% 66,1%

HOSxP 92% 84% 41,4% 77,4% 60,2% 98% 75,5%


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Figure 9: The technical debts of the SQALE characteristics of the OSHISs

These results have proved the technical potential of MediBoard. Indeed, its minimal debt

with a complexity of 2.4%, a maintainability of 21.4% and a reliability of 36.4 and a security of

24.8%; We conclude that this OSHIS insured the technical support, i.e. MediBoard has won the

third dimension challenge, which directly affects the IS service quality according to the DeLone

& McLean model.

This technological aspect in the IS presents a basis for the rest of the dimensions. Indeed,

the technical test allowed us to examine implicitly the other axes that constitute the IS. The

reliability and security of data proves the MediBoard advantage of health information. Because

hospital information is sensitive and requires a degree of confidence and protection, the

examined characteristics prove the power of the MediBoard quality in front of the rest of the

OSHISs. Not only the information quality, but also MediBoard has won the system evaluation

challenge by the technical examination of complexity and maintainability. This OSHIS proves its

strength by a minimal technical debt in the most complicated difficulty of the health system and

the management of its institutions. In other words, MediBoard marks its advantage by reducing

the complexity of the system.

Being an HIS is an obligation to respect international health standards. The HL7 standard

and others play an essential role in the patient circuit management in healthcare facilities and in

the information interoperability. The results obtained by SonarQub have selected the legal

compliance in all rules and standards as one of the examined characteristics. According to the

same characteristic, MediBoard, technically speaking, was in third place behind OpenMRS and

0

1

2

3

4

5

Reliability Security maintainability RC Complexity Documentation


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HospitalOS. The table in appendix 2 shows that MediBoard dispose of interoperability as a

detected criterion on its transport layer, connected collaboration servers and internationally

respected formats.

Finally, the evaluation of the Open Source Activity of each OSHISs was based on the

measurement of contributions and commitments. This study showed the potential of MediBoard

in the open source community by 2381 commitments and 12 contributions in 2016. This proves

that MediBoard has ensured its value and interest for the developers who contribute to its

improvement. These results, retrieved from the confirmed statistics of the OpenHub platform,

Affirms that the quality of HIS can be measured by focusing on the interest that presents this HIS

to developers and users.

Table 4: Open Source HIS Activities in 2016 (Black Duck Software, 2016)

HISs Commits Contribution

OpenEMR 1566 58

OpenMRS 522 81

MediBoard 2381 12

Open Hospital 70 2

7. Conclusion

The adoption of Open Source has been a challenge to manage first and second levels of

healthcare institutions despite problems of which suffers this sector. Our study was more than a

comparison between the chosen OSHISs; we proved also the power and quality of these ISs as

well as their services.

In this study, we proved that MediBoard is the best OSHIS to adopt. However, this

confirmation is only a result of all bibliographic study, technical evaluation and a statistical

study. According to the DeLone & McLean model and its implementations seen previously in

this paper, we still have to evaluate the information and the system qualities, by user’s feedback,

in order to confirm the total service quality.

Therefore, as a future work, we will implement completely MediBoard, propose it to a

hospital for testing its functionalities, offer the users a questionnaire that implements the DeLone

& McLean model and, finally, study the obtained results to adapt this solution following their

needs and suggestions and to improve its quality.


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APPENDICES

Appendix 1: Functional requirements of Marseille’s University Hospital versus MediBoard

(Cheick-Oumar, Dufour, Chaacho, Bouhaddou, & Fieschi, 2010)

Standard HIS features MediBoard

Care Management

Registration X

Appointments & Scheduling X

Management of Movement (Transfers) X

Care Plan Management X

e-prescription (acts, medicine) X

Nursing X

Report and Mail Management X

Logistics X

Resource Management (stocks, human, materials) X

Clinical Research, Epidemiology, Statistics and Education X

Health Information Exchange X

Laboratory management (orders)

Pharmacy management X

Imaging X

Exploratory Procedures

Emergency Department X

Surgery Department X

Admin functions

Patient identity management X

Outpatient Visits, Admissions, Stays X

Bed Management X

Evaluation of production activities (French PMSI Management) X

Billing X

Facility Management

Access Management Rights/Entitlements X

Activity Management X

Medical Economics Management X

Accounting and Record X

Human resources X

Equipment Management X

Purchasing/Inventory X

HIS Environment Management

HIS Infrastructures

Monitoring and Planning Tools

Communication Management X

Repositories and Terminology Management X

Other Features

Clinical Decision Support


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Digital Work Space X

Data Warehousing

Quality of Care Assessment X

Appendix 2: The characterizing criteria and indicators of MediBoard (MediBoard, 2014)

Indicators Results

activity Contributors 23

Commits 30834

interoperability EAI Formats HL7, HPRIM, MB-HPRIM

Collaborations Patient Identity Server

Server of Patient Mouvement

Actes Server

Transport layer FTP, SOAP

IHE PAM, PDQ, DEC

traceability Journaling logs systems

Access logs

Users logs

Code PHP 57,5%

XML 14,3%

HTML 16,5%

XML Schema 5,4%

JS 4,1%

Other 2,2%

language code common.php , [module].php

application Maintenance of translation

Translation of modules

standard Strategy of Internationalization and

localization

security server LDAP

application Authentication

Management user permission

Usability France Today, more than four million patient files are

managed with MediBoard. With more than

30,000 users and 60 facilities, the deployment

covers nearly 6,000,000 stays and 4,500,000

patients.

Switzerland

Belgium

http://mediboard.org/public/Serveur+de+Mouvement+Patient&structure=Guide+du+d%C3%A9veloppeur

http://mediboard.org/public/Serveur+d%27Actes&structure=Guide+du+d%C3%A9veloppeur

http://mediboard.org/public/PAM&structure=Guide+du+d%C3%A9veloppeur

http://mediboard.org/public/PDQ&structure=Guide+du+d%C3%A9veloppeur

http://mediboard.org/public/DEC&structure=Guide+du+d%C3%A9veloppeur

http://www.mediboard.org/public/Maintenance+de+la+traduction

http://www.mediboard.org/public/Traduction+des+modules

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